Development and Validation of an Enhanced Prediction Score for Postoperative Acute Renal Failure After Liver Resection

To enhance and validate an already pre-existing score accurately predicting post-operative acute renal failure (ARF) after hepatic surgery

We will enhance a pre-existing score predicting ARF based on pre-operative as well as intra-operative predictors.

Development process: we will identify the strongest predictors of ARF in a multivariable logistic regression model followed by a stepwise backward logistic regression analysis and bootstrapping.

Validation process: we will perform an internal validation by calibrating the prediction model as well as by k-fold cross validation (c statistics) and bootstrapping. Additionally, we will calculate the discrimination by the area under the curve (AUC).

Decision curve analysis: Furthermore we will perform a decision curve analysis to evaluate the clinical consequences of both prediction scores whether a patient with increased ARF risk would post-operative benefit of a treatment on the ICU.

Inclusion criteria

• > 18 years
• scheduled for liver surgery
• benign as well as malignant diseases

Exclusion criteria

• liver trauma
• incomplete data sets
• pre-operative chronic renal failure requiring hemodialysis